---
title: "Karura Swap Performance"
runtime: shiny
output: 
  flexdashboard::flex_dashboard:
    orientation: rows
    theme: 
      bg: "#fff"
      fg: "#000"
      primary: "#EB6864"
      base_font: !expr bslib::font_google("Prompt")
      code_font: !expr bslib::font_google("JetBrains Mono")
    source_code: embed
---

```{r, include=FALSE}

library(flexdashboard)
library(ggplot2)
library(shiny)
library(lubridate)
library(magrittr)


# To avoid error messages in plot areas
library(showtext)
showtext_auto()

knitr::opts_chunk$set(
  message = FALSE,
  warning = FALSE,
  comment = "#>"
)

# thematic::thematic_rmd(
#   font = "auto",
#   # To get the dark bg on the geom_raster()
#   sequential = thematic::sequential_gradient(fg_low = FALSE, fg_weight = 0, bg_weight = 1)
# )
# theme_set(theme_bw(base_size = 6))


# remotes::install_github("ropensci/ghql") # if package is not already installed
library(jsonlite)
library(data.table)
library("ghql")
x <- GraphqlClient$new()

endpoint <- "https://api.polkawallet.io/acala-subql"
window <- 7 # days to read in (latest day plus 7 day average)

# Helper function to concat
`%+%` <- function(a, b) paste0(a, b)

# Used to color the valueBoxes
getColor <- function(status) {
  ifelse(status >= 1, "success", ifelse(status >= .5, "warning", "danger"))
}

# make a client
cli <- GraphqlClient$new(
  url = endpoint,
  headers = list("Accept-Encoding: gzip, deflate, br",
                 "Content-Type: application/json",
                 "Accept: application/json",
                 "Connection: keep-alive",
                 "DNT: 1",
                 "Origin: https://api.polkawallet.io")
)


mindate <- today(tzone = 'UTC') - window - 1

### create a query class first
qry <- Query$new()
qry$query('dexActions', '{
  query {
    dexActions(filter: {timestamp: {greaterThanOrEqualTo: "' %+% mindate %+% '"}}) {
      nodes {
        timestamp
        id
        nodeId
        accountId
        type
        token0Id
        token1Id
        token0Amount
        token1Amount
        volumeUSD
        extrinsicId
        data
      }
    }
  }
}')
result <- cli$exec(qry$queries$dexActions) %>%
  fromJSON(flatten=TRUE)
res <- as.data.table(result$data$query$dexActions$nodes)

# Make sure we have 8 full days of data (compare latest day to prior 7 days)
maxdate <- mindate + days(7)
res <- res[timestamp <= maxdate]
# min(res$timestamp)
# max(res$timestamp)

# add share field to res
# d <- list()
# for (i in 1:nrow(res)) {
#   if (res[['type']][[i]] == 'swap') {
#     d[[i]] <- NA
#   } else {
#     tmp <- res$data[[i]][['value']]
#     d[[i]] <- tmp[6]
#   }
# }
# out <- unlist(d)
# res[, share := out]
res[, data := NULL]
res[, date := as.Date(timestamp)]
setorder(res, timestamp)

# Create pairs
res[, pair := paste0(res$token0Id, ":", res$token1Id)]
# Normalize pairs
res[pair == "KSM:KAR",  pair := "KAR:KSM"]
res[pair == "KSM:LKSM", pair := "LKSM:KSM"]
res[pair == "KSM:KUSD", pair := "KUSD:KSM"]
res[pair == "LKSM:KAR", pair := "KAR:LKSM"]
res[pair == "LKSM:KUSD",pair := "KUSD:LKSM"]
res[pair == "LKSM:BNC", pair := "BNC:LKSM"]
res[pair == "BNC:KAR",  pair := "KAR:BNC"]
res[pair == "BNC:LKSM", pair := "LKSM:BNC"]
res[pair == "BNC:KUSD", pair := "KUSD:BNC"]
res[pair == "KAR:KUSD", pair := "KUSD:KAR"]
res[pair == "BNC:KSM",  pair := "KSM:BNC"]

# res[type == 'swap', .N, by = pair]

# Number active users
activeUsers <- res[!duplicated(accountId), .N, by = date] %>%
  setnames(c("Date","Active Users"))

activeUsersPair <- res[!duplicated(accountId), .N, by = .(pair, date)] %>%
  setnames(c("Pair","Date","Active Users")) %>%
  setorder("Pair","Date")

activeUsersPairStatus <- round(tail(activeUsers$`Active Users`, 1) / mean(head(activeUsers$`Active Users`, window - 1)), 1)

# Number of trades
trades <- res[type == 'swap', .N, by = date] %>%
  setnames(c("Date","Trades"))

tradesPair <- res[type == 'swap', .N, by = .(pair, date)] %>%
  setnames(c("Pair","Date","Trades")) %>%
  setorder("Pair","Date")

# Avg trades per user
avgTrade <- merge(trades, activeUsers, by = 'Date')
avgTrade[, `Trades per user` := round(Trades / `Active Users`, 1)]

avgTradePair <- merge(tradesPair, activeUsersPair, by = c('Pair', 'Date'))
avgTradePair[, `Trades per user` := round(Trades / `Active Users`, 1)] %>%
  setorder("Pair","Date")

# Trading Volume
tradeVolume <- res[type == 'swap', sum(as.numeric(volumeUSD) / 1e12 / 1e6), by = date] %>%
  setnames(c("Date","Trading Volume"))

tradeVolumePair <- res[type == 'swap', sum(as.numeric(volumeUSD) / 1e12 / 1e6), by = .(pair, date)] %>%
  setnames(c("Pair","Date","Trading Volume")) %>%
  setorder("Pair","Date")

# Fees
fees <- res[type == 'swap', sum(as.numeric(volumeUSD) / 1e12 / 1e6) * .003, by = date] %>%
  setnames(c("Date","Fees"))

feesPair <- res[type == 'swap', sum(as.numeric(volumeUSD) / 1e12 / 1e6) * .003, by = .(pair, date)] %>%
  setnames(c("Pair","Date","Fees")) %>%
  setorder("Pair","Date")

# helper function
calc <- function(pair) {

  if (pair == "ALL") {  
    
    d_activeUsers <- activeUsers
    d_trades <- trades
    d_avgTrade <- avgTrade
    d_tradeVolume <- tradeVolume
    d_fees <- fees

    activeUsersAvg <- mean(head(activeUsers$`Active Users`, window - 1))
    activeUsersStatus <- round(tail(activeUsers$`Active Users`, 1) / activeUsersAvg, 1)
    
    tradesAvg <- mean(head(trades$`Trades`, window - 1))
    tradesStatus <- round(tail(trades$`Trades`, 1) / tradesAvg, 1)
    
    avgTradeAvg <- mean(head(avgTrade$`Trades per user`, window - 1))
    avgTradeStatus <- round(tail(avgTrade$`Trades per user`, 1) / avgTradeAvg, 1)
    
    tradeVolumeAvg <- mean(head(tradeVolume$`Trading Volume`, window - 1))
    tradeVolumeStatus <- round(tail(tradeVolume$`Trading Volume`, 1) / tradeVolumeAvg, 1)
    
    feesAvg <- mean(head(fees$`Fees`, window - 1))
    feesStatus <- round(tail(fees$`Fees`, 1) / feesAvg, 1)

  } else {

    d_activeUsers <- activeUsersPair[Pair == pair]
    d_trades <- tradesPair[Pair == pair]
    d_avgTrade <- avgTradePair[Pair == pair]
    d_tradeVolume <- tradeVolumePair[Pair == pair]
    d_fees <- feesPair[Pair == pair]

    activeUsersAvg <- mean(head(d_activeUsers$`Active Users`, window - 1))
    activeUsersStatus <- round(tail(d_activeUsers$`Active Users`, 1) / activeUsersAvg, 1)
    
    tradesAvg <- mean(head(d_trades$`Trades`, window - 1))
    tradesStatus <- round(tail(d_trades$`Trades`, 1) / tradesAvg, 1)
    
    avgTradeAvg <- mean(head(d_avgTrade$`Trades per use`, window - 1))
    avgTradeStatus <- round(tail(d_avgTrade$`Trades per user`, 1) / avgTradeAvg, 1)
    
    tradeVolumeAvg <- mean(head(d_tradeVolume$`Trading Volume`, window - 1))
    tradeVolumeStatus <- round(tail(d_tradeVolume$`Trading Volume`, 1) / tradeVolumeAvg, 1)
    
    feesAvg <- mean(head(d_fees$`Fees`, window - 1))
    feesStatus <- round(tail(d_fees$`Fees`, 1) / feesAvg, 1)

  } 

    return(list(d_activeUsers = d_activeUsers,
                d_trades = d_trades,
                d_avgTrade = d_avgTrade,
                d_tradeVolume = d_tradeVolume,
                d_fees = d_fees,
                activeUsersAvg = activeUsersAvg, 
                activeUsersStatus = activeUsersStatus,
                tradesAvg = tradesAvg, 
                tradesStatus = tradesStatus,
                avgTradeAvg = avgTradeAvg, 
                avgTradeStatus = avgTradeStatus,
                tradeVolumeAvg = tradeVolumeAvg, 
                tradeVolumeStatus = tradeVolumeStatus,
                feesAvg = feesAvg, 
                feesStatus = feesStatus))
                
}

```

# Aggregate

## test
```{r}
pair <- "ALL"
pair0 <- calc(pair)
mypair = pair
```




Performance measures are ratio of most recent day versus average of the prior `r window` days, based on `r res[type == 'swap', .N]` observations for pair `r pair` from `r min(res$timestamp)` to `r max(res$timestamp)` according to data extracted from [SubQuery Network](https://subquery.network/).

## Value Boxes {data-width=200}

### Active Users 

```{r}
pair <- "ALL"
pair0 <- calc(pair)

valueBox(pair0$activeUsersStatus, caption = "Active Users (" %+% pair %+% ")", color = getColor(pair0$activeUsersStatus))
```

### Trades

```{r}
valueBox(pair0$tradesStatus, caption = "Trades", color = getColor(pair0$tradesStatus))
```

### Trades per user

```{r}
valueBox(pair0$avgTradeStatus, caption = "Average Trades per User", color = getColor(pair0$avgTradeStatus))
```

### Trading volume

```{r}
valueBox(pair0$tradeVolumeStatus, caption = "Trading Volume (USD)", color = getColor(pair0$tradeVolumeStatus))
```

---

## Column {style="height:100pc;"}

### Active Users

```{r}
p <- barplot(height = pair0$d_activeUsers$`Active Users`, names = pair0$d_activeUsers$Date, 
          col=rgb(0.8,0.1,0.1,0.6),
          ylab="", 
          las=2) +
        abline(h = pair0$activeUsersAvg)
renderPlot(p)
```

### Trades

```{r}
p <- barplot(height = pair0$d_trades$`Trades`, names = pair0$d_trades$Date, 
          col=rgb(0.8,0.1,0.1,0.6),
          ylab="", 
          las=2) + 
        abline(h = pair0$tradesAvg)
renderPlot(p)
```

### Average Trades per User

```{r}
p <- barplot(height = pair0$d_avgTrade$`Trades per user`, names = pair0$d_avgTrade$Date, 
          col=rgb(0.8,0.1,0.1,0.6),
          ylab="", 
          las=2) + 
        abline(h = pair0$avgTradeAvg)
renderPlot(p)
```

### Trading Volume in USD

```{r}
p <- barplot(height = pair0$d_tradeVolume$`Trading Volume`, names = pair0$d_tradeVolume$Date, 
          col=rgb(0.8,0.1,0.1,0.6),
          ylab="", 
          las=2) + 
        abline(h = pair0$tradeVolumeAvg)
renderPlot(p)
```

# KAR:KSM

## test
```{r}
pair <- "KAR:KSM"
pair0 <- calc(pair)
mypair = pair
```




Performance measures are ratio of most recent day versus average of the prior `r window` days, based on `r res[pair == mypair & type == 'swap', .N]` observations for pair `r pair` from `r min(res$timestamp)` to `r max(res$timestamp)` according to data extracted from [SubQuery Network](https://subquery.network/).

## Value Boxes {data-width=200}

### Active Users 

```{r}
valueBox(pair0$activeUsersStatus, caption = "Active Users (" %+% pair %+% ")", color = getColor(pair0$activeUsersStatus))
```

### Trades

```{r}
valueBox(pair0$tradesStatus, caption = "Trades", color = getColor(pair0$tradesStatus))
```

### Trades per user

```{r}
valueBox(pair0$avgTradeStatus, caption = "Average Trades per User", color = getColor(pair0$avgTradeStatus))
```

### Trading volume

```{r}
valueBox(pair0$tradeVolumeStatus, caption = "Trading Volume (USD)", color = getColor(pair0$tradeVolumeStatus))
```

---

## Column {style="height:100pc;"}

### Active Users

```{r, fig.showtext=TRUE}
p <- barplot(height = pair0$d_activeUsers$`Active Users`, names = pair0$d_activeUsers$Date, 
          col=rgb(0.8,0.1,0.1,0.6),
          ylab="", 
          las=2) +
        abline(h = pair0$activeUsersAvg)
renderPlot(p)
```

### Trades

```{r, fig.showtext=TRUE}
p <- barplot(height = pair0$d_trades$`Trades`, names = pair0$d_trades$Date, 
          col=rgb(0.8,0.1,0.1,0.6),
          ylab="", 
          las=2) + 
        abline(h = pair0$tradesAvg)
renderPlot(p)
```

### Average Trades per User

```{r, fig.showtext=TRUE}
p <- barplot(height = pair0$d_avgTrade$`Trades per user`, names = pair0$d_avgTrade$Date, 
          col=rgb(0.8,0.1,0.1,0.6),
          ylab="", 
          las=2) + 
        abline(h = pair0$avgTradeAvg)
renderPlot(p)
```

### Trading Volume in USD

```{r}
p <- barplot(height = pair0$d_tradeVolume$`Trading Volume`, names = pair0$d_tradeVolume$Date, 
          col=rgb(0.8,0.1,0.1,0.6),
          ylab="", 
          las=2) + 
        abline(h = pair0$tradeVolumeAvg)
renderPlot(p)
```

# KUSD:KSM

## test
```{r}
pair <- "KUSD:KSM"
pair0 <- calc(pair)
mypair = pair
```




Performance measures are ratio of most recent day versus average of the prior `r window` days, based on `r res[pair == mypair & type == 'swap', .N]` observations for pair `r pair` from `r min(res$timestamp)` to `r max(res$timestamp)` according to data extracted from [SubQuery Network](https://subquery.network/).

## Value Boxes {data-width=200}

### Active Users 

```{r}
valueBox(pair0$activeUsersStatus, caption = "Active Users (" %+% pair %+% ")", color = getColor(pair0$activeUsersStatus))
```

### Trades

```{r}
valueBox(pair0$tradesStatus, caption = "Trades", color = getColor(pair0$tradesStatus))
```

### Trades per user

```{r}
valueBox(pair0$avgTradeStatus, caption = "Average Trades per User", color = getColor(pair0$avgTradeStatus))
```

### Trading volume

```{r}
valueBox(pair0$tradeVolumeStatus, caption = "Trading Volume (USD)", color = getColor(pair0$tradeVolumeStatus))
```

---

## Column {style="height:100pc;"}

### Active Users

```{r, fig.showtext=TRUE}
p <- barplot(height = pair0$d_activeUsers$`Active Users`, names = pair0$d_activeUsers$Date, 
          col=rgb(0.8,0.1,0.1,0.6),
          ylab="", 
          las=2) +
        abline(h = pair0$activeUsersAvg)
renderPlot(p)
```

### Trades

```{r, fig.showtext=TRUE}
p <- barplot(height = pair0$d_trades$`Trades`, names = pair0$d_trades$Date, 
          col=rgb(0.8,0.1,0.1,0.6),
          ylab="", 
          las=2) + 
        abline(h = pair0$tradesAvg)
renderPlot(p)
```

### Average Trades per User

```{r, fig.showtext=TRUE}
p <- barplot(height = pair0$d_avgTrade$`Trades per user`, names = pair0$d_avgTrade$Date, 
          col=rgb(0.8,0.1,0.1,0.6),
          ylab="", 
          las=2) + 
        abline(h = pair0$avgTradeAvg)
renderPlot(p)
```

### Trading Volume in USD

```{r}
p <- barplot(height = pair0$d_tradeVolume$`Trading Volume`, names = pair0$d_tradeVolume$Date, 
          col=rgb(0.8,0.1,0.1,0.6),
          ylab="", 
          las=2) + 
        abline(h = pair0$tradeVolumeAvg)
renderPlot(p)
```

# KUSD:KAR

## test
```{r}
pair <- "KUSD:KAR"
pair0 <- calc(pair)
mypair = pair
```




Performance measures are ratio of most recent day versus average of the prior `r window` days, based on `r res[pair == mypair & type == 'swap', .N]` observations for pair `r pair` from `r min(res$timestamp)` to `r max(res$timestamp)` according to data extracted from [SubQuery Network](https://subquery.network/).

## Value Boxes {data-width=200}

### Active Users 

```{r}
valueBox(pair0$activeUsersStatus, caption = "Active Users (" %+% pair %+% ")", color = getColor(pair0$activeUsersStatus))
```

### Trades

```{r}
valueBox(pair0$tradesStatus, caption = "Trades", color = getColor(pair0$tradesStatus))
```

### Trades per user

```{r}
valueBox(pair0$avgTradeStatus, caption = "Average Trades per User", color = getColor(pair0$avgTradeStatus))
```

### Trading volume

```{r}
valueBox(pair0$tradeVolumeStatus, caption = "Trading Volume (USD)", color = getColor(pair0$tradeVolumeStatus))
```

---

## Column {style="height:100pc;"}

### Active Users

```{r, fig.showtext=TRUE}
p <- barplot(height = pair0$d_activeUsers$`Active Users`, names = pair0$d_activeUsers$Date, 
          col=rgb(0.8,0.1,0.1,0.6),
          ylab="", 
          las=2) +
        abline(h = pair0$activeUsersAvg)
renderPlot(p)
```

### Trades

```{r, fig.showtext=TRUE}
p <- barplot(height = pair0$d_trades$`Trades`, names = pair0$d_trades$Date, 
          col=rgb(0.8,0.1,0.1,0.6),
          ylab="", 
          las=2) + 
        abline(h = pair0$tradesAvg)
renderPlot(p)
```

### Average Trades per User

```{r, fig.showtext=TRUE}
p <- barplot(height = pair0$d_avgTrade$`Trades per user`, names = pair0$d_avgTrade$Date, 
          col=rgb(0.8,0.1,0.1,0.6),
          ylab="", 
          las=2) + 
        abline(h = pair0$avgTradeAvg)
renderPlot(p)
```

### Trading Volume in USD

```{r}
p <- barplot(height = pair0$d_tradeVolume$`Trading Volume`, names = pair0$d_tradeVolume$Date, 
          col=rgb(0.8,0.1,0.1,0.6),
          ylab="", 
          las=2) + 
        abline(h = pair0$tradeVolumeAvg)
renderPlot(p)
```

# LKSM:KSM

## test
```{r}
pair <- "LKSM:KSM"
pair0 <- calc(pair)
mypair = pair
```




Performance measures are ratio of most recent day versus average of the prior `r window` days, based on `r res[pair == mypair & type == 'swap', .N]` observations for pair `r pair` from `r min(res$timestamp)` to `r max(res$timestamp)` according to data extracted from [SubQuery Network](https://subquery.network/).

## Value Boxes {data-width=200}

### Active Users 

```{r}
valueBox(pair0$activeUsersStatus, caption = "Active Users (" %+% pair %+% ")", color = getColor(pair0$activeUsersStatus))
```

### Trades

```{r}
valueBox(pair0$tradesStatus, caption = "Trades", color = getColor(pair0$tradesStatus))
```

### Trades per user

```{r}
valueBox(pair0$avgTradeStatus, caption = "Average Trades per User", color = getColor(pair0$avgTradeStatus))
```

### Trading volume

```{r}
valueBox(pair0$tradeVolumeStatus, caption = "Trading Volume (USD)", color = getColor(pair0$tradeVolumeStatus))
```

---

## Column {style="height:100pc;"}

### Active Users

```{r, fig.showtext=TRUE}
p <- barplot(height = pair0$d_activeUsers$`Active Users`, names = pair0$d_activeUsers$Date, 
          col=rgb(0.8,0.1,0.1,0.6),
          ylab="", 
          las=2) +
        abline(h = pair0$activeUsersAvg)
renderPlot(p)
```

### Trades

```{r, fig.showtext=TRUE}
p <- barplot(height = pair0$d_trades$`Trades`, names = pair0$d_trades$Date, 
          col=rgb(0.8,0.1,0.1,0.6),
          ylab="", 
          las=2) + 
        abline(h = pair0$tradesAvg)
renderPlot(p)
```

### Average Trades per User

```{r, fig.showtext=TRUE}
p <- barplot(height = pair0$d_avgTrade$`Trades per user`, names = pair0$d_avgTrade$Date, 
          col=rgb(0.8,0.1,0.1,0.6),
          ylab="", 
          las=2) + 
        abline(h = pair0$avgTradeAvg)
renderPlot(p)
```

### Trading Volume in USD

```{r}
p <- barplot(height = pair0$d_tradeVolume$`Trading Volume`, names = pair0$d_tradeVolume$Date, 
          col=rgb(0.8,0.1,0.1,0.6),
          ylab="", 
          las=2) + 
        abline(h = pair0$tradeVolumeAvg)
renderPlot(p)
```

# KSM:BNC

## test
```{r}
pair <- "KSM:BNC"
pair0 <- calc(pair)
mypair = pair
```




Performance measures are ratio of most recent day versus average of the prior `r window` days, based on `r res[pair == mypair & type == 'swap', .N]` observations for pair `r pair` from `r min(res$timestamp)` to `r max(res$timestamp)` according to data extracted from [SubQuery Network](https://subquery.network/).

## Value Boxes {data-width=200}

### Active Users 

```{r}
valueBox(pair0$activeUsersStatus, caption = "Active Users (" %+% pair %+% ")", color = getColor(pair0$activeUsersStatus))
```

### Trades

```{r}
valueBox(pair0$tradesStatus, caption = "Trades", color = getColor(pair0$tradesStatus))
```

### Trades per user

```{r}
valueBox(pair0$avgTradeStatus, caption = "Average Trades per User", color = getColor(pair0$avgTradeStatus))
```

### Trading volume

```{r}
valueBox(pair0$tradeVolumeStatus, caption = "Trading Volume (USD)", color = getColor(pair0$tradeVolumeStatus))
```

---

## Column {style="height:100pc;"}

### Active Users

```{r, fig.showtext=TRUE}
p <- barplot(height = pair0$d_activeUsers$`Active Users`, names = pair0$d_activeUsers$Date, 
          col=rgb(0.8,0.1,0.1,0.6),
          ylab="", 
          las=2) +
        abline(h = pair0$activeUsersAvg)
renderPlot(p)
```

### Trades

```{r, fig.showtext=TRUE}
p <- barplot(height = pair0$d_trades$`Trades`, names = pair0$d_trades$Date, 
          col=rgb(0.8,0.1,0.1,0.6),
          ylab="", 
          las=2) + 
        abline(h = pair0$tradesAvg)
renderPlot(p)
```

### Average Trades per User

```{r, fig.showtext=TRUE}
p <- barplot(height = pair0$d_avgTrade$`Trades per user`, names = pair0$d_avgTrade$Date, 
          col=rgb(0.8,0.1,0.1,0.6),
          ylab="", 
          las=2) + 
        abline(h = pair0$avgTradeAvg)
renderPlot(p)
```

### Trading Volume in USD

```{r}
p <- barplot(height = pair0$d_tradeVolume$`Trading Volume`, names = pair0$d_tradeVolume$Date, 
          col=rgb(0.8,0.1,0.1,0.6),
          ylab="", 
          las=2) + 
        abline(h = pair0$tradeVolumeAvg)
renderPlot(p)
```

# KUSD:LKSM

## test
```{r}
pair <- "KUSD:LKSM"
pair0 <- calc(pair)
mypair = pair
```




Performance measures are ratio of most recent day versus average of the prior `r window` days, based on `r res[pair == mypair & type == 'swap', .N]` observations for pair `r pair` from `r min(res$timestamp)` to `r max(res$timestamp)` according to data extracted from [SubQuery Network](https://subquery.network/).

## Value Boxes {data-width=200}

### Active Users 

```{r}
valueBox(pair0$activeUsersStatus, caption = "Active Users (" %+% pair %+% ")", color = getColor(pair0$activeUsersStatus))
```

### Trades

```{r}
valueBox(pair0$tradesStatus, caption = "Trades", color = getColor(pair0$tradesStatus))
```

### Trades per user

```{r}
valueBox(pair0$avgTradeStatus, caption = "Average Trades per User", color = getColor(pair0$avgTradeStatus))
```

### Trading volume

```{r}
valueBox(pair0$tradeVolumeStatus, caption = "Trading Volume (USD)", color = getColor(pair0$tradeVolumeStatus))
```

---

## Column {style="height:100pc;"}

### Active Users

```{r, fig.showtext=TRUE}
p <- barplot(height = pair0$d_activeUsers$`Active Users`, names = pair0$d_activeUsers$Date, 
          col=rgb(0.8,0.1,0.1,0.6),
          ylab="", 
          las=2) +
        abline(h = pair0$activeUsersAvg)
renderPlot(p)
```

### Trades

```{r, fig.showtext=TRUE}
p <- barplot(height = pair0$d_trades$`Trades`, names = pair0$d_trades$Date, 
          col=rgb(0.8,0.1,0.1,0.6),
          ylab="", 
          las=2) + 
        abline(h = pair0$tradesAvg)
renderPlot(p)
```

### Average Trades per User

```{r, fig.showtext=TRUE}
p <- barplot(height = pair0$d_avgTrade$`Trades per user`, names = pair0$d_avgTrade$Date, 
          col=rgb(0.8,0.1,0.1,0.6),
          ylab="", 
          las=2) + 
        abline(h = pair0$avgTradeAvg)
renderPlot(p)
```

### Trading Volume in USD

```{r}
p <- barplot(height = pair0$d_tradeVolume$`Trading Volume`, names = pair0$d_tradeVolume$Date, 
          col=rgb(0.8,0.1,0.1,0.6),
          ylab="", 
          las=2) + 
        abline(h = pair0$tradeVolumeAvg)
renderPlot(p)
```

# KUSD:BNC

## test
```{r}
pair <- "KUSD:BNC"
pair0 <- calc(pair)
mypair = pair
```




Performance measures are ratio of most recent day versus average of the prior `r window` days, based on `r res[pair == mypair & type == 'swap', .N]` observations for pair `r pair` from `r min(res$timestamp)` to `r max(res$timestamp)` according to data extracted from [SubQuery Network](https://subquery.network/).

## Value Boxes {data-width=200}

### Active Users 

```{r}
valueBox(pair0$activeUsersStatus, caption = "Active Users (" %+% pair %+% ")", color = getColor(pair0$activeUsersStatus))
```

### Trades

```{r}
valueBox(pair0$tradesStatus, caption = "Trades", color = getColor(pair0$tradesStatus))
```

### Trades per user

```{r}
valueBox(pair0$avgTradeStatus, caption = "Average Trades per User", color = getColor(pair0$avgTradeStatus))
```

### Trading volume

```{r}
valueBox(pair0$tradeVolumeStatus, caption = "Trading Volume (USD)", color = getColor(pair0$tradeVolumeStatus))
```

---

## Column {style="height:100pc;"}

### Active Users

```{r, fig.showtext=TRUE}
p <- barplot(height = pair0$d_activeUsers$`Active Users`, names = pair0$d_activeUsers$Date, 
          col=rgb(0.8,0.1,0.1,0.6),
          ylab="", 
          las=2) +
        abline(h = pair0$activeUsersAvg)
renderPlot(p)
```

### Trades

```{r, fig.showtext=TRUE}
p <- barplot(height = pair0$d_trades$`Trades`, names = pair0$d_trades$Date, 
          col=rgb(0.8,0.1,0.1,0.6),
          ylab="", 
          las=2) + 
        abline(h = pair0$tradesAvg)
renderPlot(p)
```

### Average Trades per User

```{r, fig.showtext=TRUE}
p <- barplot(height = pair0$d_avgTrade$`Trades per user`, names = pair0$d_avgTrade$Date, 
          col=rgb(0.8,0.1,0.1,0.6),
          ylab="", 
          las=2) + 
        abline(h = pair0$avgTradeAvg)
renderPlot(p)
```

### Trading Volume in USD

```{r}
p <- barplot(height = pair0$d_tradeVolume$`Trading Volume`, names = pair0$d_tradeVolume$Date, 
          col=rgb(0.8,0.1,0.1,0.6),
          ylab="", 
          las=2) + 
        abline(h = pair0$tradeVolumeAvg)
renderPlot(p)
```

# KAR:LKSM

## test
```{r}
pair <- "KAR:LKSM"
pair0 <- calc(pair)
mypair = pair
```




Performance measures are ratio of most recent day versus average of the prior `r window` days, based on `r res[pair == mypair & type == 'swap', .N]` observations for pair `r pair` from `r min(res$timestamp)` to `r max(res$timestamp)` according to data extracted from [SubQuery Network](https://subquery.network/).

## Value Boxes {data-width=200}

### Active Users 

```{r}
valueBox(pair0$activeUsersStatus, caption = "Active Users (" %+% pair %+% ")", color = getColor(pair0$activeUsersStatus))
```

### Trades

```{r}
valueBox(pair0$tradesStatus, caption = "Trades", color = getColor(pair0$tradesStatus))
```

### Trades per user

```{r}
valueBox(pair0$avgTradeStatus, caption = "Average Trades per User", color = getColor(pair0$avgTradeStatus))
```

### Trading volume

```{r}
valueBox(pair0$tradeVolumeStatus, caption = "Trading Volume (USD)", color = getColor(pair0$tradeVolumeStatus))
```

---

## Column {style="height:100pc;"}

### Active Users

```{r, fig.showtext=TRUE}
p <- barplot(height = pair0$d_activeUsers$`Active Users`, names = pair0$d_activeUsers$Date, 
          col=rgb(0.8,0.1,0.1,0.6),
          ylab="", 
          las=2) +
        abline(h = pair0$activeUsersAvg)
renderPlot(p)
```

### Trades

```{r, fig.showtext=TRUE}
p <- barplot(height = pair0$d_trades$`Trades`, names = pair0$d_trades$Date, 
          col=rgb(0.8,0.1,0.1,0.6),
          ylab="", 
          las=2) + 
        abline(h = pair0$tradesAvg)
renderPlot(p)
```

### Average Trades per User

```{r, fig.showtext=TRUE}
p <- barplot(height = pair0$d_avgTrade$`Trades per user`, names = pair0$d_avgTrade$Date, 
          col=rgb(0.8,0.1,0.1,0.6),
          ylab="", 
          las=2) + 
        abline(h = pair0$avgTradeAvg)
renderPlot(p)
```

### Trading Volume in USD

```{r}
p <- barplot(height = pair0$d_tradeVolume$`Trading Volume`, names = pair0$d_tradeVolume$Date, 
          col=rgb(0.8,0.1,0.1,0.6),
          ylab="", 
          las=2) + 
        abline(h = pair0$tradeVolumeAvg)
renderPlot(p)
```

# KAR:BNC

## test
```{r}
pair <- "KAR:BNC"
pair0 <- calc(pair)
mypair = pair
```




Performance measures are ratio of most recent day versus average of the prior `r window` days, based on `r res[pair == mypair & type == 'swap', .N]` observations for pair `r pair` from `r min(res$timestamp)` to `r max(res$timestamp)` according to data extracted from [SubQuery Network](https://subquery.network/).

## Value Boxes {data-width=200}

### Active Users 

```{r}
valueBox(pair0$activeUsersStatus, caption = "Active Users (" %+% pair %+% ")", color = getColor(pair0$activeUsersStatus))
```

### Trades

```{r}
valueBox(pair0$tradesStatus, caption = "Trades", color = getColor(pair0$tradesStatus))
```

### Trades per user

```{r}
valueBox(pair0$avgTradeStatus, caption = "Average Trades per User", color = getColor(pair0$avgTradeStatus))
```

### Trading volume

```{r}
valueBox(pair0$tradeVolumeStatus, caption = "Trading Volume (USD)", color = getColor(pair0$tradeVolumeStatus))
```

---

## Column {style="height:100pc;"}

### Active Users

```{r, fig.showtext=TRUE}
p <- barplot(height = pair0$d_activeUsers$`Active Users`, names = pair0$d_activeUsers$Date, 
          col=rgb(0.8,0.1,0.1,0.6),
          ylab="", 
          las=2) +
        abline(h = pair0$activeUsersAvg)
renderPlot(p)
```

### Trades

```{r, fig.showtext=TRUE}
p <- barplot(height = pair0$d_trades$`Trades`, names = pair0$d_trades$Date, 
          col=rgb(0.8,0.1,0.1,0.6),
          ylab="", 
          las=2) + 
        abline(h = pair0$tradesAvg)
renderPlot(p)
```

### Average Trades per User

```{r, fig.showtext=TRUE}
p <- barplot(height = pair0$d_avgTrade$`Trades per user`, names = pair0$d_avgTrade$Date, 
          col=rgb(0.8,0.1,0.1,0.6),
          ylab="", 
          las=2) + 
        abline(h = pair0$avgTradeAvg)
renderPlot(p)
```

### Trading Volume in USD

```{r}
p <- barplot(height = pair0$d_tradeVolume$`Trading Volume`, names = pair0$d_tradeVolume$Date, 
          col=rgb(0.8,0.1,0.1,0.6),
          ylab="", 
          las=2) + 
        abline(h = pair0$tradeVolumeAvg)
renderPlot(p)
```

# LKSM:BNC

## test
```{r}
pair <- "LKSM:BNC"
pair0 <- calc(pair)
mypair = pair
```




Performance measures are ratio of most recent day versus average of the prior `r window` days, based on `r res[pair == mypair & type == 'swap', .N]` observations for pair `r pair` from `r min(res$timestamp)` to `r max(res$timestamp)` according to data extracted from [SubQuery Network](https://subquery.network/).

## Value Boxes {data-width=200}

### Active Users 

```{r}
valueBox(pair0$activeUsersStatus, caption = "Active Users (" %+% pair %+% ")", color = getColor(pair0$activeUsersStatus))
```

### Trades

```{r}
valueBox(pair0$tradesStatus, caption = "Trades", color = getColor(pair0$tradesStatus))
```

### Trades per user

```{r}
valueBox(pair0$avgTradeStatus, caption = "Average Trades per User", color = getColor(pair0$avgTradeStatus))
```

### Trading volume

```{r}
valueBox(pair0$tradeVolumeStatus, caption = "Trading Volume (USD)", color = getColor(pair0$tradeVolumeStatus))
```

---

## Column {style="height:100pc;"}

### Active Users

```{r, fig.showtext=TRUE}
p <- barplot(height = pair0$d_activeUsers$`Active Users`, names = pair0$d_activeUsers$Date, 
          col=rgb(0.8,0.1,0.1,0.6),
          ylab="", 
          las=2) +
        abline(h = pair0$activeUsersAvg)
renderPlot(p)
```

### Trades

```{r, fig.showtext=TRUE}
p <- barplot(height = pair0$d_trades$`Trades`, names = pair0$d_trades$Date, 
          col=rgb(0.8,0.1,0.1,0.6),
          ylab="", 
          las=2) + 
        abline(h = pair0$tradesAvg)
renderPlot(p)
```

### Average Trades per User

```{r, fig.showtext=TRUE}
p <- barplot(height = pair0$d_avgTrade$`Trades per user`, names = pair0$d_avgTrade$Date, 
          col=rgb(0.8,0.1,0.1,0.6),
          ylab="", 
          las=2) + 
        abline(h = pair0$avgTradeAvg)
renderPlot(p)
```

### Trading Volume in USD

```{r}
p <- barplot(height = pair0$d_tradeVolume$`Trading Volume`, names = pair0$d_tradeVolume$Date, 
          col=rgb(0.8,0.1,0.1,0.6),
          ylab="", 
          las=2) + 
        abline(h = pair0$tradeVolumeAvg)
renderPlot(p)
```

# Data 

## Row {style="height:100pc;"}








### data

```{r, fig.width=19, fig.height=19}
library(tidyverse)
library(DT)
create_dt <- function(x){
  DT::datatable(x,
                extensions = 'Buttons',
                options = list(dom = 'Blfrtip',
                               buttons = c('copy', 'csv', 'excel'),
                               lengthMenu = list(c(25,50,-1),
                                                 c(25,50,"All"))))
}
create_dt(res)
```